Scientific Research Publishing

Deep Reinforcement Learning for Phishing Detection with Transformer-Based Semantic Features ()

Phishing is a form of cybercrime in which people are deceived into exposing their personal information which can result in ...
Investopedia

Stepwise Regression Explained: Uses, Benefits, and Drawbacks

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...
Investopedia

Understanding Econometrics: Key Models and Methods Explained

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...
Frontiers

A support vector regression-based prediction model for offshore broadcasting signal propagation

Broadcasting plays an important role in offshore information transmission because of its stability and long-distance propagation characteristics. To improve propagation prediction in the offshore ...
SciELO

A multinomial logistic regression model for public transportation use in a medium-sized Brazilian city

Paper aims This paper addresses the influence of socioeconomic, quality, built environment, and safety variables on the demand for public transportation service. Originality This study covers a ...
Scientific Research Publishing

Heart Disease Prediction: A Logistic Regression Approach ()

1 School of Computing and Data Science, Wentworth Institute of Technology, Boston, USA. 2 Department of Computer Science and Quantitative Methods, Austin Peay State University, Clarksville, USA. 3 ...
GitHub

AutoClean - Automated Data Preprocessing & Cleaning

It is commonly known among Data Scientists that data cleaning and preprocessing make up a major part of a data science project. And, you will probably agree with me that it is not the most exciting ...
Nature

A comparative study of explainable ensemble learning and logistic regression for predicting in-hospital mortality in the emergency department

This study addresses the challenges associated with emergency department (ED) overcrowding and emphasizes the need for efficient risk stratification tools to identify high-risk patients for early ...
Frontiers

Greedy knot selection algorithm for restricted cubic spline regression

Non-linear regression modeling is common in epidemiology for prediction purposes or estimating relationships between predictor and response variables. Restricted cubic spline (RCS) regression is one ...
InfoWorld

The engines of AI: Machine learning algorithms explained

Machine learning and deep learning have been widely embraced, and even more widely misunderstood. In this article, I’ll step back and explain both machine learning and deep learning in basic terms, ...